Image-based hemodynamic simulations for intracranial aneurysms: the impact of complex vasculature.

PURPOSE: Hemodynamics play an important role in the assessment of intracranial aneurysm (IA) development and rupture risk. The purpose of this study was to examine the impact of complex vasculatures onto the intra-vessel and intra-aneurysmal blood flow. METHODS: Complex segmentation of a subject-specific, 60-outlet and 3-inlet circle of Willis model captured with 7T magnetic resonance imaging was performed. This model was trimmed to a 10-outlet model version. Two patient-specific IAs were added onto both models yielding two pathological versions, and image-based blood flow simulations of the four resulting cases were carried out. To capture the differences between complex and trimmed model, time-averaged and centerline velocities were compared. The assessment of intra-saccular blood flow within the IAs involved the evaluation of wall shear stresses (WSS) at the IA wall and neck inflow rates (NIR). RESULTS: Lower flow values are observed in the majority of the complex model. However, at specific locations (left middle cerebral artery 0.5 m/s, left posterior cerebral artery 0.25 m/s), higher flow rates were visible when compared to the trimmed counterpart. Furthermore, at the centerlines the total velocity values reveal differences up to 0.15 m/s. In the IAs, the reduction in the neck inflow rate and WSS in the complex model was observed for the first IA (IA-A δNIRmean = - 0.07ml/s, PCA.l δWSSmean = - 0.05 Pa). The second IA featured an increase in the neck inflow rate and WSS (IA-B δNIRmean = 0.04 ml/s, PCA.l δWSSmean = 0.07 Pa). CONCLUSION: Both the magnitude and shape of the flow distribution vary depending on the model's complexity. The magnitude is primarily influenced by the global vessel model, while the shape is determined by the local structure. Furthermore, intra-aneurysmal flow strongly depends on the location in the vessel tree, emphasizing the need for complex model geometries for realistic hemodynamic assessment and rupture risk analysis.

In vitro and in silico assessment of flow modulation after deploying the Contour Neurovascular System in intracranial aneurysm models.

BACKGROUND: The novel Contour Neurovascular System (Contour) has been reported to be efficient and safe for the treatment of intracranial, wide-necked bifurcation aneurysms. Flow in the aneurysm and posterior cerebral arteries (PCAs) after Contour deployment has not been analyzed in detail yet. However, this information is crucial for predicting aneurysm treatment outcomes. METHODS: Time-resolved three-dimensional velocity maps in 14 combinations of patient-based basilar tip aneurysm models with and without Contour devices (sizes between 5 and 14 mm) were analyzed using four-dimensionsal (4D) flow MRI and numerical/image-based flow simulations. A complex virtual processing pipeline was developed to mimic the experimental shape and position of the Contour together with the simulations. RESULTS: On average, the Contour significantly reduced intra-aneurysmal flow velocity by 67% (mean w/ = 0.03m/s; mean w/o = 0.12m/s; p-value=0.002), and the time-averaged wall shear stress by more than 87% (mean w/ = 0.17Pa; mean w/o = 1.35Pa; p-value=0.002), as observed by numerical simulations. Furthermore, a significant reduction in flow (P<0.01) was confirmed by the neck inflow rate, kinetic energy, and inflow concentration index after Contour deployment. Notably, device size has a stronger effect on reducing flow than device positioning. However, positioning affected flow in the PCAs, while being robust in effectively reducing flow. CONCLUSIONS: This study showed the high efficacy of the Contour device in reducing flow within aneurysms regardless of the exact position. However, we observed an effect on the flow in PCAs, which needs to be investigated further.

Integrated biophysical matching of bacterial nanocellulose coronary artery bypass grafts towards bioinspired artery typical functions.

Revascularization via coronary artery bypass grafting (CABG) to treat cardiovascular disease is established as one of the most important lifesaving surgical techniques worldwide. But the shortage in functionally self-adaptive autologous arteries leads to circumstances where the clinical reality must deal with fighting pathologies coming from the mismatching biophysical functionality of more available venous grafts. Synthetic biomaterial-based CABG grafts did not make it to the market yet, what is mostly due to technical hurdles in matching biophysical properties to the complex demands of the CABG niche. But bacterial Nanocellulose (BNC) Hydrogels derived by growing biofilms hold a naturally integrative character in function-giving properties by its freedom in designing form and intrinsic fiber architecture. In this study we use this integral to combine impacts on the luminal fiber matrix, biomechanical properties and the reciprocal stimulation of microtopography and induced flow patterns, to investigate biomimetic and artificial designs on their bio-functional effects. Therefore, we produced tubular BNC-hydrogels at distinctive designs, characterized the structural and biomechanical properties and subjected them to in vitro endothelial colonization in bioreactor assisted perfusion cultivation. Results showed clearly improved functional properties and gave an indication of successfully realized stimulation by artery-typical helical flow patterns.

Is Accurate Lumen Segmentation More Important than Outlet Boundary Condition in Image-Based Blood Flow Simulations for Intracranial Aneurysms?

PURPOSE: Image-based blood flow simulations are increasingly used to investigate the hemodynamics in intracranial aneurysms (IAs). However, a strong variability in segmentation approaches as well as the absence of individualized boundary conditions (BCs) influence the quality of these simulation results leading to imprecision and decreased reliability. This study aims to analyze these influences on relevant hemodynamic parameters within IAs. METHODS: As a follow-up study of an international multiple aneurysms challenge, the segmentation results of five IAs differing in size and location were investigated. Specifically, five possible outlet BCs were considered in each of the IAs. These are comprised of the zero-pressure condition (BC1), a flow distribution based on Murray's law with the exponents n = 2 (BC2) and n = 3 (BC3) as well as two advanced flow-splitting models considering the real vessels by including circular cross sections (BC4) or anatomical cross sections (BC5), respectively. In total, 120 time-dependent blood flow simulations were analyzed qualitatively and quantitatively, focusing on five representative intra-aneurysmal flow and five shear parameters such as vorticity and wall shear stress. RESULTS: The outlet BC variation revealed substantial differences. Higher shear stresses (up to Δ9.69 Pa), intrasaccular velocities (up to Δ0.15 m/s) and vorticities (up to Δ629.22 1/s) were detected when advanced flow-splitting was applied compared to the widely used zero-pressure BC. The tendency of outlets BCs to over- or underestimate hemodynamic parameters is consistent across different segmentations of a single aneurysm model. Segmentation-induced variability reaches Δ19.58 Pa, Δ0.42 m/s and Δ957.27 1/s, respectively. Excluding low fidelity segmentations, however, (a) reduces the deviation drastically (>43%) and (b) leads to a lower impact of the outlet BC on hemodynamic predictions. CONCLUSION: With a more realistic lumen segmentation, the influence of the BC on the resulting hemodynamics is decreased. A realistic lumen segmentation can be ensured, e.g., by using high-resolved 2D images. Furthermore, the selection of an advanced outflow-splitting model is advised and the use of a zero-pressure BC and BC based on Murray's law with exponent n = 3 should be avoided.

CFD simulations of inhalation through a subject-specific human larynx - Impact of the unilateral vocal fold immobility.

BACKGROUND: The larynx of the human respiratory tract plays a vital role in breathing and voice production. Both can be influenced by functional and/or morphological changes of the larynx, e.g., immobility of one or both vocal folds (VF). The immobile VF can become stationary in different positions such as the median, paramedian, intermediate or lateral position. The impact of unilateral vocal fold immobility (UVFI) on inhalation is the focus of this study. METHODS: Transient numerical simulations of the inhalation process in patient-specific airways are performed. Five configurations are considered: paramedian and intermediate VF positions on the left and right, and healthy. Large eddy simulations are used to describe the complex laryngeal turbulent flow. Airway resistance, power loss, and spectral entropy are calculated to quantify the work of inspiration and evaluate flow regimes. RESULTS: The laryngeal jet intensity and flow disturbance increase with the severity of immobility. In comparison to the healthy configuration, UVFI with right/left intermediate and right/left paramedian VF position increases the airway resistance over the oropharynx to the trachea by 69%/58% and 310%/285%, respectively. When the entire respiratory system is considered, an increase of up to 48% is estimated. Spectral entropy increases of up to 2.5 times indicate higher turbulence levels due to UVFI. CONCLUSIONS: Surgery of immobile VF aims to improve glottis closure. However, this can have a negative impact on breathing efficiency. To that end, this study provides initial insights into the conflicting objectives of open versus closed VFs.

Central moments multiple relaxation time LBM for hemodynamic simulations in intracranial aneurysms: An in-vitro validation study using PIV and PC-MRI.

The lattice Boltzmann method (LBM) has recently emerged as an efficient alternative to classical Navier-Stokes solvers. This is particularly true for hemodynamics in complex geometries. However, in its most basic formulation, i.e. with the so-called single relaxation time (SRT) collision operator, it has been observed to have a limited stability domain in the Courant/Fourier space, strongly constraining the minimum time-step and grid size. The development of improved collision models such as the multiple relaxation time (MRT) operator in central moments space has tremendously widened the stability domain, while allowing to overcome a number of other well-documented artifacts, therefore opening the door for simulations over a wider range of grid and time-step sizes. The present work focuses on implementing and validating a specific collision operator, the central Hermite moments multiple relaxation time model with the full expansion of the equilibrium distribution function, to simulate blood flows in intracranial aneurysms. The study further proceeds with a validation of the numerical model through different test-cases and against experimental measurements obtained via stereoscopic particle image velocimetry (PIV) and phase-contrast magnetic resonance imaging (PC-MRI). For a patient-specific aneurysm both PIV and PC-MRI agree fairly well with the simulation. Finally, low-resolution simulations were shown to be able to capture blood flow information with sufficient accuracy, as demonstrated through both qualitative and quantitative analysis of the flow field while leading to strongly reduced computation times. For instance in the case of the patient-specific configuration, increasing the grid-size by a factor of two led to a reduction of computation time by a factor of 14 with very good similarity indices still ranging from 0.83 to 0.88.

Hemodynamic Data Assimilation in a Subject-specific Circle of Willis Geometry.

PURPOSE: The anatomy of the circle of Willis (CoW), the brain's main arterial blood supply system, strongly differs between individuals, resulting in highly variable flow fields and intracranial vascularization patterns. To predict subject-specific hemodynamics with high certainty, we propose a data assimilation (DA) approach that merges fully 4D phase-contrast magnetic resonance imaging (PC-MRI) data with a numerical model in the form of computational fluid dynamics (CFD) simulations. METHODS: To the best of our knowledge, this study is the first to provide a transient state estimate for the three-dimensional velocity field in a subject-specific CoW geometry using DA. High-resolution velocity state estimates are obtained using the local ensemble transform Kalman filter (LETKF). RESULTS: Quantitative evaluation shows a considerable reduction (up to 90%) in the uncertainty of the velocity field state estimate after the data assimilation step. Velocity values in vessel areas that are below the resolution of the PC-MRI data (e.g., in posterior communicating arteries) are provided. Furthermore, the uncertainty of the analysis-based wall shear stress distribution is reduced by a factor of 2 for the data assimilation approach when compared to the CFD model alone. CONCLUSION: This study demonstrates the potential of data assimilation to provide detailed information on vascular flow, and to reduce the uncertainty in such estimates by combining various sources of data in a statistically appropriate fashion.

Super-resolution and denoising of 4D-Flow MRI using physics-Informed deep neural nets.

BACKGROUND AND OBJECTIVE: Time resolved three-dimensional phase contrast magnetic resonance imaging (4D-Flow MRI) has been used to non-invasively measure blood velocities in the human vascular system. However, issues such as low spatio-temporal resolution, acquisition noise, velocity aliasing, and phase-offset artifacts have hampered its clinical application. In this research, we developed a purely data-driven method for super-resolution and denoising of 4D-Flow MRI. METHODS: The flow velocities, pressure, and the MRI image magnitude are modeled as a patient-specific deep neural net (DNN). For training, 4D-Flow MRI images in the complex Cartesian space are used to impose data-fidelity. Physics of fluid flow is imposed through regularization. Creative loss function terms have been introduced to handle noise and super-resolution. The trained patient-specific DNN can be sampled to generate noise-free high-resolution flow images. The proposed method has been implemented using the TensorFlow DNN library and tested on numerical phantoms and validated in-vitro using high-resolution particle image velocitmetry (PIV) and 4D-Flow MRI experiments on transparent models subjected to pulsatile flow conditions. RESULTS: In case of numerical phantoms, we were able to increase spatial resolution by a factor of 100 and temporal resolution by a factor of 5 compared to the simulated 4D-Flow MRI. There is an order of magnitude reduction of velocity normalized root mean square error (vNRMSE). In case of the in-vitro validation tests with PIV as reference, there is similar improvement in spatio-temporal resolution. Although the vNRMSE is reduced by 50%, the method is unable to negate a systematic bias with respect to the reference PIV that is introduced by the 4D-Flow MRI measurement. CONCLUSIONS: This work has demonstrated the feasibility of using the readily available machinery of deep learning to enhance 4D-Flow MRI using a purely data-driven method. Unlike current state-of-the-art methods, the proposed method is agnostic to geometry and boundary conditions and therefore eliminates the need for tedious tasks such as accurate image segmentation for geometry, image registration, and estimation of boundary flow conditions. Arbitrary regions of interest can be selected for processing. This work will lead to user-friendly analysis tools that will enable quantitative hemodynamic analysis of vascular diseases in a clinical setting.

Transient flow prediction in an idealized aneurysm geometry using data assimilation.

Hemodynamic simulations are restricted by modeling assumptions and uncertain initial and boundary conditions, whereas Phase-Contrast Magnetic Resonance Imaging (PC-MRI) data is affected by measurement noise and artifacts. To overcome the limitations of both techniques, the current study uses a Localization Ensemble Transform Kalman Filter (LETKF) to fully incorporate noisy, low-resolution Phase-Contrast MRI data into an ensemble of high-resolution numerical simulations. The analysis output provides an improved state estimate of the three-dimensional blood flow field in an intracranial aneurysm model. Benchmark measurements are carried out in a silicone phantom model of an idealized aneurysm under pulsatile inflow conditions. Validation is ensured with high-resolution Particle Imaging Velocimetry (PIV) obtained in the symmetry plane of the same geometry. Two data assimilation approaches are introduced, which differ in their way to propagate the ensemble members in time. In both cases the velocity noise is significantly reduced over the whole cardiac cycle. Quantitative and qualitative results indicate an improvement of the flow field prediction in comparison to the raw measurement data. Although biased measurement data reveal a systematic deviation from the truth, the LETKF is able to account for stochastically distributed errors. Through the implementation of the data assimilation step, physical constraints are introduced into the raw measurement data. The resulting, realistic high-resolution flow field can be readily used to assess further patient-specific parameters in addition to the velocity distribution, such as wall shear stress or pressure.

A review on the reliability of hemodynamic modeling in intracranial aneurysms: why computational fluid dynamics alone cannot solve the equation.

Computational blood flow modeling in intracranial aneurysms (IAs) has enormous potential for the assessment of highly resolved hemodynamics and derived wall stresses. This results in an improved knowledge in important research fields, such as rupture risk assessment and treatment optimization. However, due to the requirement of assumptions and simplifications, its applicability in a clinical context remains limited.This review article focuses on the main aspects along the interdisciplinary modeling chain and highlights the circumstance that computational fluid dynamics (CFD) simulations are embedded in a multiprocess workflow. These aspects include imaging-related steps, the setup of realistic hemodynamic simulations, and the analysis of multidimensional computational results. To condense the broad knowledge, specific recommendations are provided at the end of each subsection.Overall, various individual substudies exist in the literature that have evaluated relevant technical aspects. In this regard, the importance of precise vessel segmentations for the simulation outcome is emphasized. Furthermore, the accuracy of the computational model strongly depends on the specific research question. Additionally, standardization in the context of flow analysis is required to enable an objective comparison of research findings and to avoid confusion within the medical community. Finally, uncertainty quantification and validation studies should always accompany numerical investigations.In conclusion, this review aims for an improved awareness among physicians regarding potential sources of error in hemodynamic modeling for IAs. Although CFD is a powerful methodology, it cannot provide reliable information, if pre- and postsimulation steps are inaccurately carried out. From this, future studies can be critically evaluated and real benefits can be differentiated from results that have been acquired based on technically inaccurate procedures.

Stent-induced vessel deformation after intracranial aneurysm treatment - A hemodynamic pilot study.

BACKGROUND: Stent-assisted coiling has become an important treatment option for intracranial aneurysms. However, studies have shown that this procedure can lead to the deformation of the local vasculature. Its effect on intra-aneurysmal hemodynamics still remains unclear. METHODS: Pre- and post-interventional image data of three representative middle cerebral artery aneurysms are considered in this study. This includes virtually deployed stents and coils. To evaluate the proportional effect of a) vessel deformation, b) stent deployment, and c) coil placement, 24 unsteady blood flow simulations were carried out focusing on the separated effects related to intra-aneurysmal hemodynamics. Four flow parameters (velocity within the aneurysm sac, aneurysm neck inflow rate, inflow concentration index, and ostium inflow area) and four shear parameters (wall shear stress, normalized wall shear stress, shear concentration index, and high shear area) were quantified. RESULTS: All of the considered flow and shear parameters, except for the shear concentration index, were clearly reduced due to treatment. Coiling and stenting caused a distinct and smaller neck inflow rate, respectively, while the impact of deformation was inconsistent among the aneurysms. Overall, coiling appears to have the strongest impact on local hemodynamics. CONCLUSION: Stent-induced vessel deformation has a clear impact on intra-aneurysmal hemodynamics. This effect is neglected by the majority of previous studies, which consider the pre-interventional state for investigating the relation of stents and hemodynamics. The findings of this pilot study suggest that while stent-assisted coiling can lead to an improved hemodynamic situation, undesired flow conditions may occur in response to treatment.

Multiple Aneurysms AnaTomy CHallenge 2018 (MATCH)-Phase Ib: Effect of morphology on hemodynamics.

BACKGROUND: Image-based blood flow simulations have been increasingly applied to investigate intracranial aneurysm (IA) hemodynamics. However, the acceptance among physicians remains limited due to the high variability in the underlying assumptions and quality of results. METHODS: To evaluate the vessel segmentation as one of the most important sources of error, the international Multiple Aneurysms AnaTomy CHallenge 2018 (MATCH) was announced. 26 research groups from 13 different countries segmented three datasets, which contained five IAs in total. Based on these segmentations, 73 time-dependent blood flow simulations under consistent conditions were carried out. Afterwards, relevant flow and shear parameters (e.g., neck inflow rate, parent vessel flow rate, spatial mean velocity, and wall shear stress) were analyzed both qualitatively and quantitatively. RESULTS: Regarding the entire vasculature, the variability of the segmented vessel radius is 0.13 mm, consistent and independent of the local vessel radius. However, the centerline velocity shows increased variability in more distal vessels. Focusing on the aneurysms, clear differences in morphological and hemodynamic parameters were observed. The quantification of the segmentation-induced variability showed approximately a 14% difference among the groups for the parent vessel flow rate. Regarding the mean aneurysmal velocity and the neck inflow rate, a variation of 30% and 46% was observed, respectively. Finally, time-averaged wall shear stresses varied between 28% and 51%, depending on the aneurysm in question. CONCLUSIONS: MATCH reveals the effect of state-of-the-art segmentation algorithms on subsequent hemodynamic simulations for IA research. The observed variations may lead to an inappropriate interpretation of the simulation results and thus, can lead to inappropriate conclusions by physicians. Therefore, accurate segmentation of the region of interest is necessary to obtain reliable and clinically helpful flow information.

Multiple Aneurysms AnaTomy CHallenge 2018 (MATCH)-phase II: rupture risk assessment.

PURPOSE: Assessing the rupture probability of intracranial aneurysms (IAs) remains challenging. Therefore, hemodynamic simulations are increasingly applied toward supporting physicians during treatment planning. However, due to several assumptions, the clinical acceptance of these methods remains limited. METHODS: To provide an overview of state-of-the-art blood flow simulation capabilities, the Multiple Aneurysms AnaTomy CHallenge 2018 (MATCH) was conducted. Seventeen research groups from all over the world performed segmentations and hemodynamic simulations to identify the ruptured aneurysm in a patient harboring five IAs. Although simulation setups revealed good similarity, clear differences exist with respect to the analysis of aneurysm shape and blood flow results. Most groups (12/71%) included morphological and hemodynamic parameters in their analysis, with aspect ratio and wall shear stress as the most popular candidates, respectively. RESULTS: The majority of groups (7/41%) selected the largest aneurysm as being the ruptured one. Four (24%) of the participating groups were able to correctly select the ruptured aneurysm, while three groups (18%) ranked the ruptured aneurysm as the second most probable. Successful selections were based on the integration of clinically relevant information such as the aneurysm site, as well as advanced rupture probability models considering multiple parameters. Additionally, flow characteristics such as the quantification of inflow jets and the identification of multiple vortices led to correct predictions. CONCLUSIONS: MATCH compares state-of-the-art image-based blood flow simulation approaches to assess the rupture risk of IAs. Furthermore, this challenge highlights the importance of multivariate analyses by combining clinically relevant metadata with advanced morphological and hemodynamic quantification.

Multiple Aneurysms AnaTomy CHallenge 2018 (MATCH): uncertainty quantification of geometric rupture risk parameters.

BACKGROUND: Geometric parameters have been proposed for prediction of cerebral aneurysm rupture risk. Predicting the rupture risk for incidentally detected unruptured aneurysms could help clinicians in their treatment decision. However, assessment of geometric parameters depends on several factors, including the spatial resolution of the imaging modality used and the chosen reconstruction procedure. The aim of this study was to investigate the uncertainty of a variety of previously proposed geometric parameters for rupture risk assessment, caused by variability of reconstruction procedures. MATERIALS: 26 research groups provided segmentations and surface reconstructions of five cerebral aneurysms as part of the Multiple Aneurysms AnaTomy CHallenge (MATCH) 2018. 40 dimensional and non-dimensional geometric parameters, describing aneurysm size, neck size, and irregularity of aneurysm shape, were computed. The medians as well as the absolute and relative uncertainties of the parameters were calculated. Additionally, linear regression analysis was performed on the absolute uncertainties and the median parameter values. RESULTS: A large variability of relative uncertainties in the range between 3.9 and 179.8% was found. Linear regression analysis indicates that some parameters capture similar geometric aspects. The lowest uncertainties < 6% were found for the non-dimensional parameters isoperimetric ratio, convexity ratio, and ellipticity index. Uncertainty of 2D and 3D size parameters was significantly higher than uncertainty of 1D parameters. The most extreme uncertainties > 80% were found for some curvature parameters. CONCLUSIONS: Uncertainty analysis is essential on the road to clinical translation and use of rupture risk prediction models. Uncertainty quantification of geometric rupture risk parameters provided by this study may help support development of future rupture risk prediction models.

Novel feature-based visualization of the unsteady blood flow in intracranial aneurysms with the help of proper orthogonal decomposition (POD).

The recognition and interpretation of pulsatile subject-specific blood flow is a challenging task. Animations of various quantities - such as blood flow velocity, pressure, or wall shear stress - can be depicted to visualize the complex time-varying flow features, normally in a region of interest. Traditional visualization methods however can hardly convey the dynamic information of the system. Proper orthogonal decomposition (POD), a mathematical tool, allows for the complex spatial-temporal information to be decomposed into individual spatial modes. In the present study, the most energetic blood flow features are extracted with the help of POD analysis. The first mode, representing the most energetic flow feature, characterizes the temporal mean of the flow velocity. It is considered as the primary flow. The second most energetic mode corresponds to the secondary flow features. Visualization techniques combining the primary and the secondary flows are suggested in the present paper in order to create a simplified visualization of the unsteady blood flow. The methods are presented for intracranial aneurysms for both measured as well as simulated data, illustrating the application for Phase-Contrast Magnetic Resonance Imaging (PC-MRI) and computational fluid dynamics (CFD) results.

Quantitative assessment of 4D hemodynamics in cerebral aneurysms using proper orthogonal decomposition.

BACKGROUND AND PURPOSE: The comparison of different time-varying three-dimensional hemodynamic data (4D) is a formidable task. The purpose of this study is to investigate the potential of the proper orthogonal decomposition (POD) for a quantitative assessment. METHODS: The complex spatial-temporal flow information was analyzed using proper orthogonal decomposition to reduce the complexity of the system. PC-MRI blood flow measurements and computational fluid dynamic simulations of two subject-specific IAs were used to compare the different flow modalities. The concept of Modal Assurance Criterion (MAC) provided a further detailed objective characterization of the most energetic individual modes. RESULTS: The most energetic flow modes were qualitatively compared by visual inspection. The distribution of the kinetic energy on the modes was used to quantitatively compare pulsatile flow data, where the most energetic mode was associated to approximately 90% of the total kinetic energy. This distribution was incorporated in a single measure, termed spectral entropy, showing good agreement especially for Case 1. CONCLUSION: The proposed quantitative POD-based technique could be a valuable tool to reduce the complexity of the time-dependent hemodynamic data and to facilitate an easy comparison of 4D flows, e.g., for validation purposes.

3DRA Reconstruction of Intracranial Aneurysms - How does Voxel Size Influences Morphologic and Hemodynamic Parameters.

Three-dimensional shape analysis and imagebased hemodynamic simulations are widely used to assess the individual rupture risk of intracranial aneurysms. However, the quality of those results highly depends on pre-simulative working steps including image reconstruction and segmentation. Within this study, three patient-specific aneurysms were reconstructed using three different voxel sizes (0.1 mm, 0.3 mm, 0.5 mm). Afterwards, 3D segmentations and time-dependent blood flow simulations were carried out to evaluate the impact of the reconstruction size. The results indicate that overall all voxel sizes lead to a qualitatively good agreement with respect to the aneurysm surfaces. However, deviations occur regarding the neck representation as well as the consideration of perforating arteries. Further, morphological differences lead to clear hemodynamic variations, especially for shear force predictions. The findings indicate that depending on the desired analysis, careful reconstruction parameter selection is required. Particularly, for quantitative morphology and blood flow studies, the early step of reconstruction can have a crucial effect on subsequent results.

Multiple Aneurysms AnaTomy CHallenge 2018 (MATCH): Phase I: Segmentation.

PURPOSE: Advanced morphology analysis and image-based hemodynamic simulations are increasingly used to assess the rupture risk of intracranial aneurysms (IAs). However, the accuracy of those results strongly depends on the quality of the vessel wall segmentation. METHODS: To evaluate state-of-the-art segmentation approaches, the Multiple Aneurysms AnaTomy CHallenge (MATCH) was announced. Participants carried out segmentation in three anonymized 3D DSA datasets (left and right anterior, posterior circulation) of a patient harboring five IAs. Qualitative and quantitative inter-group comparisons were carried out with respect to aneurysm volumes and ostia. Further, over- and undersegmentation were evaluated based on highly resolved 2D images. Finally, clinically relevant morphological parameters were calculated. RESULTS: Based on the contributions of 26 participating groups, the findings reveal that no consensus regarding segmentation software or underlying algorithms exists. Qualitative similarity of the aneurysm representations was obtained. However, inter-group differences occurred regarding the luminal surface quality, number of vessel branches considered, aneurysm volumes (up to 20%) and ostium surface areas (up to 30%). Further, a systematic oversegmentation of the 3D surfaces was observed with a difference of approximately 10% to the highly resolved 2D reference image. Particularly, the neck of the ruptured aneurysm was overrepresented by all groups except for one. Finally, morphology parameters (e.g., undulation and non-sphericity) varied up to 25%. CONCLUSIONS: MATCH provides an overview of segmentation methodologies for IAs and highlights the variability of surface reconstruction. Further, the study emphasizes the need for careful processing of initial segmentation results for a realistic assessment of clinically relevant morphological parameters.

Virtual stenting of intracranial aneurysms: A pilot study for the prediction of treatment success based on hemodynamic simulations.

Endovascular treatment of intracranial aneurysms using flow-diverting devices has revolutionized the treatment of large and complex lesions due to its minimally invasive nature and potential clinical outcomes. However, incomplete or delayed occlusion and persistent intracranial aneurysm growth are still an issue for up to one-third of the patients. We evaluated two patients with intracranial aneurysm located at the internal carotid artery who were treated with flow-diverting devices and had opposite outcomes. Both patients presented with similar aneurysms and were treated with the same device, but after a 1-year follow-up, one case presented with complete occlusion (Case 1) and the other required further treatment (Case 2). To reproduce the interventions, virtual stents were deployed and blood flow simulations were carried out using the respective patient-specific geometries. Afterward, hemodynamic metrics such as aneurysmal inflow reduction, wall shear stresses, oscillatory shear, and inflow concentration indices were quantified. The hemodynamic simulations reveal that for both cases, the neck inflow was clearly reduced due to the therapy (Case 1: 19%, Case 2: 35%). In addition, relevant hemodynamic parameters such as time-averaged wall shear stress (Case 1: 35.6%, Case 2: 57%) and oscillatory shear (Case 1: 33.1%, Case 2: 26.7%) were decreased considerably. However, although stronger relative reductions occurred in the unsuccessful case, the absolute flow values in the successful case were approximately halved. The findings demonstrate that a high relative effect of endovascular devices is not necessarily associated with the desired treatment outcome. Instead, it appears that a successful intracranial aneurysm therapy requires a certain patient-specific inflow threshold.

Tomographic particle image velocimetry for the validation of hemodynamic simulations in an intracranial aneurysm.

Image-based blood flow simulations can provide detailed hemodynamic information in diseased vessels such as intracranial aneurysms. However, validation is essential to evaluate the accuracy of these computations and further improve their acceptance among physicians. In this regard, tomographic particle image velocimetry was used to measure the flow characteristics in a patient specific aneurysm phantom model. Additionally, computational fluid dynamics (CFD) simulations were carried out using a well accepted commercial software package and a clinical research prototype, respectively. The comparison between in-vitro measurement and in-silico computations reveals a good qualitative agreement. Further, computations based on classical CFD agreed well with results from a clinical research prototype. Hence, the results of this study demonstrate the usability of numerical methods to obtain realistic blood flow predictions in a clinical context.